With the rapid development of Internet-of-Things (IoT) devices and mobile communication
technologies, Multi-access Edge Computing (MEC) has emerged as a promising paradigm …

Recently, there has been a substantial interest in on-device Machine Learning (ML) models
to provide intelligence for the Internet of Things (IoT) applications such as image …

Abstract Federated Learning (FL), Artificial Intelligence (AI), and Explainable Artificial
Intelligence (XAI) are the most trending and exciting technology in the intelligent healthcare …

Federated Learning is a distributed, privacy-preserving machine learning model that is
gaining more attention these days. Federated Learning has a vast number of applications in …

Over-the-air federated learning (OTA-FL) is a distributed machine learning technique where
multiple devices collaboratively train a shared model without sharing their raw data with a …

The development of AI applications, especially in large-scale wireless networks, is growing
exponentially, alongside the size and complexity of the architectures used. Particularly …

Federated Learning (FL) facilitates collaborative training of a shared global model without
exposing clients' private data. In practical FL systems, clients (eg, edge servers …

Encounters between humans and wildlife often lead to injuries, especially in remote
wilderness regions, and highways. Therefore, animal detection is a vital safety and wildlife …

In recent years, deep learning (DL) models have demonstrated remarkable achievements
on non-trivial tasks such as speech recognition, image processing, and natural language …

Due to the privacy breach risks and data aggregation of traditional centralized machine
learning (ML) approaches, applications, data and computing power are being pushed from …